Using wavelet tools to analyse seasonal variations from InSAR time-series data: a case study of the Huangtupo landslide

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Title: Using wavelet tools to analyse seasonal variations from InSAR time-series data: a case study of the Huangtupo landslide
Authors: Tomás, Roberto | Li, Zhenhong | Lopez-Sanchez, Juan M. | Liu, Peng | Singleton, Andrew
Research Group/s: Ingeniería del Terreno y sus Estructuras (InTerEs) | Señales, Sistemas y Telecomunicación
Center, Department or Service: Universidad de Alicante. Departamento de Ingeniería Civil | Universidad de Alicante. Departamento de Física, Ingeniería de Sistemas y Teoría de la Señal | Universidad de Alicante. Instituto Universitario de Investigación Informática
Keywords: InSAR | Wavelet analysis | Continuous wavelet transform | Cross wavelet transform | Wavelet coherence | Time-series | Time-frequency space | Landslide | Triggering factors
Knowledge Area: Ingeniería del Terreno | Teoría de la Señal y Comunicaciones
Issue Date: Jun-2016
Publisher: Springer Berlin Heidelberg
Citation: Landslides. 2016, 13(3): 437-450. doi:10.1007/s10346-015-0589-y
Abstract: Synthetic aperture radar interferometry (InSAR) has proven to be a powerful tool for monitoring landslide movements with a wide spatial and temporal coverage. Interpreting landslide displacement time-series derived from InSAR techniques is a major challenge for understanding relationships between triggering factors and slope displacements. In this study, we propose the use of various wavelet tools, namely, continuous wavelet transform (CWT), cross wavelet transform (XWT) and wavelet coherence (WTC) for interpreting InSAR time-series information for a landslide. CWT enables time-series records to be analysed in time-frequency space, with the aim of identifying localized intermittent periodicities. Similarly, XWT and WTC help identify the common power and relative phase between two time-series records in time-frequency space, respectively. Statistically significant coherence and confidence levels against red noise (also known as brown noise or random walk noise) can be calculated. Taking the Huangtupo landslide (China) as an example, we demonstrate the capabilities of these tools for interpreting InSAR time-series information. The results show the Huangtupo slope is affected by an annual displacement periodicity controlled by rainfall and reservoir water level. Reservoir water level, which is completely regulated by the dam activity, is mainly in ‘anti-phase’ with natural rainfall, due to flood control in the Three Gorges Project. The seasonal displacements of the Huangtupo landslide is found to be ‘in-phase’ with respect to reservoir water level and the rainfall towards the front edge of the slope and to rainfall at the higher rear of the slope away from the reservoir.
Sponsor: R. Tomás was supported by the Generalitat Valenciana fellowship BEST-2011/225 and by the Ministry of Education, Culture and Sport trough the project PRX14/00100. Part of this work is also supported by the Spanish Ministry of Economy and Competitiveness and EU FEDER funds under project TEC2011-28201-C02-02, by the Natural Environmental Research Council (NERC) through the GAS and LICS projects (ref. NE/H001085/1 and NE/K010794/1, respectively) as well as the ESA-MOST DRAGON-3 projects (ref. 10607 and 10665).
ISSN: 1612-510X (Print) | 1612-5118 (Online)
DOI: 10.1007/s10346-015-0589-y
Language: eng
Type: info:eu-repo/semantics/article
Rights: © Springer-Verlag Berlin Heidelberg 2015. The final publication is available at Springer via
Peer Review: si
Publisher version:
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